Triple
T22770491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regnecentralen |
E563541
|
entity |
| Predicate | nativeName |
P15
|
FINISHED |
| Object | Regnecentralen |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Regnecentralen | Statement: [Regnecentralen, nativeName, Regnecentralen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Regnecentralen Context triple: [Regnecentralen, nativeName, Regnecentralen]
-
A.
Regnecentralen
chosen
Regnecentralen was a pioneering Danish computer company and research institution known for its early contributions to computer science and computing technology in Denmark.
-
B.
Kjernen
Kjernen is the main organized supporters' group of Norwegian football club Rosenborg BK, known for its passionate fan culture and vocal backing at matches.
-
C.
Syvde
Syvde is a small village in western Norway, located in the fjord landscape of Møre og Romsdal county within Vanylven Municipality.
-
D.
Pilerne
Pilerne is a village in North Goa, India, known for its scenic landscapes, salt pans, and proximity to popular coastal and urban areas like Candolim and Panaji.
-
E.
Runhällen
Runhällen is a small locality in central Sweden situated within Heby Municipality in Uppsala County.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e24554497c819080b996e071de27c2 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b5cea44819097290351da9c488d |
completed | April 29, 2026, 3:30 a.m. |
Created at: April 17, 2026, 3:27 p.m.